International Journal of Climatology最新文献

The Tibetan Plateau (TP), known as the “Asian water tower,” provides freshwater resources for hundreds of millions of people in Asia. Most of the Asian rivers, such as the Yangtze, the Jinsha, the Salween and the Brahmaputra, are generated from southeastern part of the TP (SETP). In order to explore the influences of atmospheric circulation on the precipitation over the SETP, self-organizing mapping (SOM) was utilized to identify the weather regimes (WRs) and related precipitation over the SETP and its surrounding areas. The daily scale of large-scale circulation via ERA5 were classified into nine WRs by the SOM. There are two favourable regimes (rainy WRs) and three adverse ones (rainless WRs) for the SETP precipitation among these WRs, respectively. Furthermore, water vapour transport of the WRs and the relevant effects of ENSO are investigated. The droughts and floods of SETP are determined by the interannual variations of occurred frequency of the WRs. In particular, the SETP is flooded in the years with frequent occurrence of the rainy WRs and vice versa. The occurrence of WRs is closely related to the phase state of ENSO. The 9th WR (SOM9) and the 4th WR (SOM4) are separately occurred more frequently in the El Niño and the La Niña years. Regulation of ENSO on the SETP precipitation are effective through its influences on the state of atmospheric circulation, that is, frequency of various WRs. It implies that the occurred frequency of WRs is modulated by the climate systems and results in the interannual variations of precipitation over the SETP.

The increase in extreme precipitation with global warming (GW) and associated uncertainties are major challenges for climate adaptation. To project future extreme precipitation on different time and intensity scales (return periods [RPs] from 1 to 100 a and durations from 1 h to 3 days), we use a novel convection-permitting (CP), multi-global climate model ensemble of COSMO-CLM regional simulations with a transient projection time (1971–2100) over Germany. We find an added value of the CP scale (2.8 km) with respect to the representation of hourly extreme precipitation intensities compared to the coarser scale with parametrized deep convection (7 km). In general, the return levels (RLs) calculated from the CP simulations are in better agreement with those of the conventional observation-based risk products for the region for short event durations than for longer durations, where an overestimation by the simulation-based results was found. A maximum climate change signal of 6–8.5% increase per degree of GW is projected within the CP ensemble, with the largest changes expected for short durations and long RPs. Analysis of the uncertainty in the climate change signal shows a substantial residual standard deviation of a linear approximation, highlighting the need for transient data sets instead of time-slice experiments to increase confidence in the estimates. Furthermore, the ensemble spread is found to be smallest for intensities of short duration, where changes are expected to be based mainly on thermodynamic contributions. The ensemble spread is larger for long, multi-day durations, where a stronger dependence on the dynamical component is ascribed. In addition, an increase in spatial variance of the RLs with GW implies a more variable future climate and points to an increasing importance of accounting for uncertainties.

Tibetan Plateau vortices (TPVs) are major rainfall triggers over the Tibetan Plateau (TP), which often cause heavy rainfalls in eastern China when moving off the TP. Although previous studies have revealed the climatic characteristics of TPVs at different timescales, the relationships between the different activity characteristics of TPVs are unclear. In this study, TPVs during May to August during 1998–2020 are objectively identified based on ERA5 reanalysis data, and connections between the initial states of TPVs and their subsequent activities, as well as the connections between the states of TPVs before moving off the TP and those after moving off are investigated. It is reported that the TPVs generated over the central and western TP north of 32° N, particularly near 84° E, 35° N, are always stronger, maintain longer and move further in their subsequent life, and the TPVs generated near 95° E over the eastern TP move eastwards the fastest. The initial intensity of most TPVs is smaller than 1.1 × 10⁻⁴ s⁻¹; regarding these TPVs, their average duration, movement distance and movement speed exhibit an initial decrease followed by an increase as the initial intensity rises. The stronger the TPVs initially are, the stronger they are in their entire lifetime. The majority of the moving-off TPVs are generated over the eastern TP; generally, TPVs generated further east with a large initial intensity are more likely to move off the TP. After moving off the TP, most TPVs remain in the same movement direction as before; if the TPVs are strong when they are over the TP, they tend to be strong, last long and move eastwards further after moving off the TP, and vice versa.

Crowdsourced observation networks are typically much more dense than those maintained by National Meteorological Services, and sample a much wider range of local climates. This offers an opportunity to build observed climatologies that are more representative of lived experience, particularly in cities. This study provides a worked example to show their potential for improving operational climate services, and to identify the challenges to realizing that potential. To demonstrate the concept, data from personal weather stations, obtained through citizen science, are used to build an observed record of daily maximum temperatures in 2020 in Manchester (UK). This record is compared to the standard baseline used in a current climate service, showing a substantial increase in the estimated heat hazard. If such potential benefits are to be realized in a climate service, it will be necessary to first build an alternative observed baseline of decadal length and at national or international scale. This requires further work to acquire, quality-control, exposure-control and map the crowdsourced observations.

Clouds are a key element of the climate system. They play a crucial role in modulating solar radiative flux reaching the Earth's surface and influencing environmental conditions. In particular, total cloud cover (TCC) has both direct and indirect influence on agricultural production. Through dialogues with vegetable and rice producers of Northeastern Argentina (NEA), an important productive region in South-Eastern South America, the key role of cloud cover on crop yields was brought to the forefront. In this study, we present the climatology and observed long-term changes in TCC in NEA. The analyses are performed based on two independent datasets: TCC ground-based (GB) observations and satellite-based estimates from the International Satellite Cloud Climatology Project (ISCCP). The datasets cover a common period, from December 1983 to November 2016 (Satellite Period), while GB TCC observations extend further, from March 1961 to February 2021 (GB Period). To facilitate a more comprehensive examination of GB TCC, we introduce a novel Cloud Index, expressed in a familiar unit (%), which allows  the study of its temporal variations. TCC exhibits a distinct annual cycle and substantial spatial variability over NEA, consistently evident in both satellite and GB datasets. Over the Satellite Period (GB Period), we observed a decrease in NEA's TCC in both datasets (GB dataset), with seasonal variations and spatial heterogeneity. We ensured the reliability of our results by comparing the two datasets, which showed similar temporal variability, although the ISCCP Cloud Amount values were larger than the GB TCC. The described TCC climatology and observed changes have considerable implications for NEA's agricultural production and provide a robust foundation for future research. This article generates robust methodological basis for the analysis of this complex variable, a necessary step to explore the forcing of climate variability that modulates cloudiness in future research, and that could facilitate future studies in other regions of South America and the world.

Due to its size and geographical features, different average annual rainfall regimes co-exist in the Amazon basin, with distinct year-to-year variability dependent on regions within the basin. In this study, we define and explain the seasonal regional types of annual regimes, that is, years with similar seasonal anomalies. Our work is based on a 205 rain gauge network distributed over five Amazonian countries, spanning a period over 30 years. Using a spectral clustering method, we identified seven sub-regions within the basin in which annual rainfall regimes are spatially homogenous. For each sub-domain, we estimated specific parameters that characterize the rainy season (onset and demise dates, sign and duration of rainfall anomalies). Finally, using spectral analysis we identified between two and four ‘seasonal type’ of precipitation in these seven sub-domains. Most of these seasonal types are in phase with the large-scale atmospheric circulation, which explains the temporal link with rainfall anomalies. The seasonal types result of the superposition of inter-annual and intra-seasonal variability whose factors are then difficult to identify and attribute. Part of the rainfall anomalies characterizing seasonal types is related to the inter-annual variability of the sea surface temperature in the Atlantic or the Pacific oceans, especially in the northeast and southeast part of the Amazon basin, whereas in other parts, strong intra-seasonal and local factors have a larger impact. The same sign and duration of anomalies do not concomitantly affect the various regions of the Amazon basin, confirming that one mode of variability does not homogeneously affect precipitation in different parts of the basin.

This work aims to define a set of representative weather patterns for South Africa that can be utilized to support impact-based forecasting of heatwave events. Sets of weather patterns have been generated using k-means clustering on daily ERA5 reanalysis data between 1979 and 2020. Different pattern sets were generated by varying the clustering atmospheric variable, the spatial domain and the number of weather patterns. These weather patterns are evaluated using the explained variation score to assess their ability to represent the variability of the maximum daily 2m temperature (T_max,2m). The results indicate that a set of 30 weather patterns generated using mean sea-level pressure, with a clustering domain in the range 15°–34°E and 21°–36°S, provides a reasonable representation of T_max,2m variability across South Africa. The implementation of an appropriate weather pattern set into a medium-range forecasting tool has the potential to extend the prediction of high-impact weather events in South Africa, such as heatwaves, and also highlight specific impacts on the population, for example, food and water insecurity, heat exhaustion or energy and transport impacts.

The Yangtze River basin (YRB) and its southern region in China (20°–34°N, 104°–123°E, YRBSC) are highly susceptible to climate change and experience extreme hydrological events. To understand the spatial and temporal distribution of summer runoff in these regions, a statistical diagnosis method was applied using monthly mean runoff grid data, global Sea Surface Temperature (SST) data and meteorological reanalysis data from 1980 to 2022. The analysis revealed that variations in the isotropic phase within the YRBSC and the north–south inverse phase with the Yangtze River as the boundary are the main modes of summer runoff. Furthermore, a strong correlation was observed between winter SST anomalies (SSTAs) and late summer runoff in the YRBSC, as determined through singular value decomposition (SVD). In the first type of positive SSTA years, the eastward advance of the South Asian high pressure (SAH) and westward shift of the subtropical high pressure (SH) result in sufficient water vapour, strong upward movement and increased summer runoff. The second type of positive SSTA years exhibits a westward retreat of the SAH, upward movement north of 28°N, and downward movement between 20°N and 28°N. These conditions, combined with water vapour intermixing and dispersion, lead to a northward increase and southward decrease of summer runoff in the YRBSC, with the boundary at 28°N. Additionally, the study analysed the extreme drought situation observed in the YRB during the summer of 2022. The findings of this research provide valuable insights for ecological environmental protection, water resource planning and management in the region.

On August 8th, 2022, an extreme rainfall event (the 88ER) occurred over South Korea's metropolitan area and resulted in immense losses of human lives and properties. Previous study has attributed the rainfall event to the intersection of warm and cold air induced by a Northeast China Cold Vortex (NCCV) and the persistently northward displacement of the West Pacific Subtropical High (WPSH). However, in addition to dynamic drivers, understanding the moisture transport of the 88ER is likewise crucial for developing effective strategies to prevent rainstorm disasters. In this study, based on the output from a WRF model, the primary moisture sources and transport pathways of the 88ER are investigated in a Lagrangian view. The Yellow Sea and East China Sea (YSECS) are identified as the most significant moisture source region (84.42%), followed by South Korea (KR), the eastern China (EC) and Democratic People's Republic of Korea (DPRK), which contribute 12.52%, 1.52% and 1.43% of the released moisture, respectively. Furthermore, to assess the sensitivity of moisture fluxes and heavy rainfall to the sea surface temperature (SST) anomalies in the YSECS, an additional WRF model experiment is conducted in which the SST anomalies are replaced by the average SST over the past 30 years. It is found that the SST anomalies in the YSECS cause differences in atmospheric circulation, and therefore exert a strong influence on moisture transport. The SST anomalies finally enhance the moisture contribution of the YSECS by 1.72%, but decrease that over KR, EC and DPRK by 1.03%, 0.35% and 0.33%, respectively.

This article analyses the winter warm spells (WWS) that occurred in central Mediterranean over the period 1993–2022, examining the daily maximum temperatures collected at eight airport sites located in the Italian Peninsula, belonging to different climate zones. According to the definition proposed in 1999 by the Expert Team on Climate Change Detection and Indices (ETCCDI), a WWS is a sequence of at least six consecutive days when daily maximum air temperature exceeds the calendar day 90th percentile centred on a 5-day window for a base period. WWS occurring over the entire Italian territory or only over northern/central/southern Italy have been identified and related to the peculiar synoptic conditions. It was found that December is the month most prone to WWS and, on average, WWS last 9.4 days in northern Italy, 6.6 days in central Italy, and 8.5 days in southern Italy. Over the period under investigation, the Italian Peninsula experienced only one common event characterized by persistent high-pressure systems associated with air subsidence over western Mediterranean and, therefore, with exceptional warming. Finally, it has been proven that the definition of WWS proposed by ETCCDI allows to capture synoptic scale events but, in orographically complex areas such as Italy, underestimates moderate spells, which generally might have a duration of at least 3 days. Consequently, it is important to consider the possibility of reducing the period length threshold used for the detection of WWS when orographically heterogeneous regions are studied.